Methods
Summary
The project will rely on a strategy to efficiently explore and fight inequalities in food accessibility based on a GIS-based optimization routine, which identifies the optimal location of and required features (e.g size, agronomic productivity.) of agroforestry agricultural systems all over Indonesia, replacing the current monocultures (e.g rice).
To develop the GIS-based optimization framework, a variety of data will be gathered, including population distribution maps, climate variables, agrometeorology data, food production estimations and gridded friction surface data for land-based travel speed.
Challenges
A challenge for the proposed analysis and its findings consist of the potential uncertainty and error in remotely sensed observations and the scale of analysis in relation to data granularity. Additionally, while the food production estimation will try to maximise the diversification in diets patterns, it will be limited by the agrometeorology of a given area and will not assume potential substitution dynamics, e.g. temporary switches to other foods coming from abroad or distant regions within the country.
Protocols
This project has not yet shared any protocols.